Dr. Biyanka Ekanayake is a lecturer in Construction Automation and Property Technology at UTS, specialising in computer vision and generative AI key branches of Artificial Intelligence (AI). Her research and teaching are dedicated to advancing automation in the construction and property industries through AI. Recognised for her excellence in research integrated and practice-oriented teaching in AI, construction automation and property technology (PropTech), Biyanka received the 2025 UTS Vice-Chancellor���s Learning and Teaching: Early Career Teaching Award. With her professional background in Facilities Management and skills in programming, Biyanka is currently researching how generative AI (GenAI) and computer vision (image processing and analytics) can revolutionise the construction and property industries. She is experimenting on "Vision-Language AI" (Multimodal AI models). She also brings these innovative tools to learning environments giving students the opportunity to explore both the potential and ethical challenges associated with emerging technologies. She serves as the AI Lead for the School of Built Environment, focusing on the ethical and innovative integration of GenAI into School’s teaching and research practices. Biyanka is the winner of 2025 Faculty Award for Integrating Generative AI in Teaching and Learning and 2023 Faculty Award for Innovative Curriculum Design for PropTech sub-major subjects. She is a regular speaker at industry events and academic forums on AI in construction and property industries and she also delivers consultancy projects in these areas. 

Biyanka is a Guest Editor for the Special Issue in "AI in the Built Environment: Opportunities, Risks, and Future Directions" (Building Research & Information) Q1 Journal. She is the lead author of the upcoming textbook on "PropTech Education and Professional Skills in the Age of AI: Preparing Construction and Property Professionals for AI-Enabled Practice" (Routledge). 

Research portfolio

Biyanka’s core expertise in AI spans computer vision, GenAI, large language models, machine learning, deep learning, and vision-language models. Her overarching goal is to enhance automation in the construction and property sectors by enabling data-driven approaches that manage complexity and promote sustainability across the built environment. As of 2026, She is a highly cited emerging scholar in following areas with her research widely published in leading construction and property journals and presented at international conferences. 

1. Computer Vision and Deep Learning for Construction Progress Monitoring

Construction projects often suffer from inefficient progress tracking and manual reporting leading to cost overruns, delays, and poor project control. Biyanka’s doctoral research conducted at UTS addressed these inefficiencies by developing a computer vision–based AI model for automated indoor construction progress monitoring using site images and deep learning algorithms. She further translated this research into a web-based platform for construction project managers to improve real time progress management.

2. Vision-Language AI Models for Building Defect Diagnosis

Detecting and diagnosing building defects remains time-consuming and subjective, often dependent on manual inspections and expert judgment. To tackle this, Biyanka investigates multimodal AI systems, particularly vision-language models that combine images and textual data for defect detection and diagnosis and improving building inspection and maintenance strategies. Biyanka's current research builds upon her vision-based crack detection models and professional experience in the area.  
 

3. Ethical and Innovative AI in Construction and Property Practice & Education

The adoption of GenAI in the construction and property sectors has led to ethical concerns, including AI misuse, data privacy, bias, and  inaccurate content. Biyanka’s research explores how GenAI can be ethically and innovatively integrated into property technology education and industry practice. Her work provides guidelines for ethical implementation and innovation in AI adoption.

4. AI Applications for Climate Resilience in Buildings 

The construction and property sectors significantly contribute to carbon emissions, energy consumption, and resource inefficiency. Biyanka’s work applies AI-driven analytics to enhance energy efficiency, carbon reduction, and building refurbishment strategies. Her research links directly with the UN SDGs - SDG 9 (Industry, Innovation and Infrastructure) and SDG 11 (Sustainable Cities and Communities) advancing data-informed decision-making for a resilient built environment.

Recognising her expertise, she has been invited to serves as: Editorial Review Board Member, Smart and Sustainable Built Environments journal (Q1) and Construction innovation journal (Q1) and Scientific Committee Member, World Construction Symposium (Scopus Indexed). Biyanka received the Professor Gamunu Fernando Memorial Award for Best Undergraduate Dissertation in 2017 from the University of Moratuwa, Sri Lanka.

Teaching portfolio

Biyanka equips construction and property students to lead industry technological innovation through student-centred teaching, curriculum and assessment integrating technology, practice, research and industry engagement. She leads the PropTech sub-major at UTS, Australia's first program dedicated to this emerging field. UTS has integrated a distinct PropTech sub-major into their Bachelor of Construction Project Management and Bachelor of Property Economics degrees. This sub-major focuses on the integration of AI, digital tools and data analytics within the property and construction sectors, providing students with the skills and knowledge to leverage emerging technologies in collaboration with major PropTech companies in Australia. She also teaches construction management subjects  with a focus on AI in Bachelor of Construction Project Management, Australia’s most sought-after degree program in the field.

She frequently showcases her GenAI-related teaching at UTS and is often invited to lead and facilitate workshops at other universities, industry forums, and national and international conferences. Before joining UTS, she was a research scholar and visiting lecturer in buildings at University of Moratuwa, Sri Lanka.

Services and engagement
Biyanka is the AI Lead for the School of Built Environment and also serves as the Early Career Research (ECR) Representative on the Faculty Research Committee. She is also a Committee Member of the Faculty Teaching & Learning Community of Practice. As an early career academic working at the nexus of AI, data analytics, and the built environment, she is committed to helping shape the strategic research direction of the Faculty. 

Biyanka actively contributes to several key roles that enhance the quality and relevance of construction and property education at UTS and beyond. As a “Chartered Building Professional", she was elected to the NSW Chapter Committee (2024-2025) of the Australian Institute of Building (AIB), where she ensures that construction management education aligns with industry needs. She is also a member of the Property Technology Association of Australia (PropTech Association), the peak body championing the growth of technology in the property industry and education. 

As the Academic Mentor of the UTS Built Environment Student Association (2023-2026) and the School of Built Environment Representative for the Jumbunna Institute for Indigenous Education and Research, Biyanka is dedicated to fostering inclusive and supportive learning environments for the construction and property students. Her commitment to equity is further demonstrated through her involvement in the 2024 UTS Philanthropic Awards Program Working Group, which aimed to expand scholarships, prizes, internships, and mentorship opportunities to enrich the student experience. She was also part of the “Emerging Leaders” cohort in the 2024 UTS LEAD Program representing the faculty. Biyanka’s dedication to creating positive career pathways for students from diverse backgrounds reflects her broader mission to shape a more inclusive and innovative future in the construction and property sectors.